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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is K-Means clustering?
💡 Hint: Think about how data points are grouped together!
Question 2
Easy
Why is data preparation important?
💡 Hint: Consider how raw data might affect your analysis.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the primary purpose of K-Means clustering?
- To classify data points into predefined categories
- To partition data into K distinct clusters
- To reduce the dimensionality of data
💡 Hint: Think about what K represents in this context!
Question 2
True or False: Hierarchical clustering requires the number of clusters to be defined in advance.
- True
- False
💡 Hint: What gives hierarchical clustering its flexibility?
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Consider a dataset with significant noise and varying densities. Which clustering method would you choose to analyze this dataset, and why?
💡 Hint: Focus on the methods’ strengths and how they address noise.
Question 2
You have applied K-Means clustering but suspect that the number of clusters chosen was too low. What approach would you take to validate the number of clusters next time?
💡 Hint: What methods help in determining the right K?
Challenge and get performance evaluation